Do you like cartoons?I am crazy about cartoons because they are very interesting and cartoon music listens really great.I have a great time when I watch the cartoon films.
Applying visual grammar theory,this study examines representational,interactive,and compositional meanings of the giant panda in Western media cartoons related to China from 1999 to the present.Distinct phases in the ...Applying visual grammar theory,this study examines representational,interactive,and compositional meanings of the giant panda in Western media cartoons related to China from 1999 to the present.Distinct phases in the panda’s representation were identified and illustrated by cases of cartoons in major Western media.These phases trace shift of panda cartoon image from a symbol of peace and friendliness to a politicized emblem of China’s international stance.Key visual trends,such as transitivity,color symbolism,scale enlargement,and increasing compositional complexity,embody the panda’s role in shaping China’s global image and its function in international discourse.These trends reflect the panda’s transformation into a contested symbol,which mediates between China’s self-representation and Western perceptions of its geopolitical rise.By situating the analysis within the context of China’s growing global influence,this study contributes to visual and media studies,demonstrating how cultural symbols are recontextualized to reflect and shape geopolitical narratives.展开更多
Automated cartoon character recognition is crucial for applications in content indexing,filtering,and copyright protection,yet it faces a significant challenge in animated media due to high intra-class visual variabil...Automated cartoon character recognition is crucial for applications in content indexing,filtering,and copyright protection,yet it faces a significant challenge in animated media due to high intra-class visual variability,where characters frequently alter their appearance.To address this problem,we introduce the novel Kral Sakir dataset,a public benchmark of 16,725 images specifically curated for the task of multi-label cartoon character classification under these varied conditions.This paper conducts a comprehensive benchmark study,evaluating the performance of state-of-the-art pretrained Convolutional Neural Networks(CNNs),including DenseNet,ResNet,and VGG,against a custom baseline model trained from scratch.Our experiments,evaluated using metrics of F1-Score,accuracy,and Area Under the ROC Curve(AUC),demonstrate that fine-tuning pretrained models is a highly effective strategy.The best-performing model,DenseNet121,achieved an F1-Score of 0.9890 and an accuracy of 0.9898,significantly outperforming our baseline CNN(F1-Score of 0.9545).The findings validate the power of transfer learning for this domain and establish a strong performance benchmark.The introduced dataset provides a valuable resource for future research into developing robust and accurate character recognition systems.展开更多
Animation creates a vivid, virtual world and expands the scope of human imagination. In this study, we investigated the time-courses of brain responses related to the evaluation of the attractiveness of cartoon faces ...Animation creates a vivid, virtual world and expands the scope of human imagination. In this study, we investigated the time-courses of brain responses related to the evaluation of the attractiveness of cartoon faces using the event-related potential （ERP） technique. The results demonstrated that N170 amplitude was higher for attractive than for unattractive cartoon faces in males, while the opposite was found in females. Facial attractiveness notably modulated the late positive component （LPC）, which might reflect the task-related process of aesthetic appraisal of beauty. The mean LPC amplitude in males was significantly higher for attractive cartoon faces than for unattractive faces, while the LPC amplitude in females did not significantly differ between attractive and unattractive cartoon faces. Moreover, the paint mode （computer graphics, gouache, and stick figure） modulated the early encoding of facial structures and the late evaluative process. The early modulation effect by paint mode may be related to the spatial frequency of the pictures. The processing speed and intensity in females were both higher than those in males. In conclusion, our study, for the first time, reported ERP modulation based on the assessment of cartoon facial attractiveness, suggesting the facilitated selection of attractiveness information at the early stage, and that the attentional enhancement of attractive faces at the late stage only exists in males. This suggests that men＇s brains are hard-wired to be sensitive to facial beauty, even in cartoons.展开更多
BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons comb...BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.展开更多
The aim of this study was to investigate the temporal cortical activation patterns underlying different stages of humor comprehension (e.g., detection of incongruity stage, resolution of incongruity stage, and affecti...The aim of this study was to investigate the temporal cortical activation patterns underlying different stages of humor comprehension (e.g., detection of incongruity stage, resolution of incongruity stage, and affective stage). Event-related potentials (ERPs) were measured when 16 subjects were apprehending cartoon pictures including humorous, non-humorous and unrelated items. Results showed that both humorous and unrelated items elicited a more negative ERP deflection (N500-800) than non-humorous ones between 500 - 800 ms, which might reflect detection to incongruent element during humor apprehension. Then, both humorous and non-humorous items elicited a more positive ERP deflection (P800-1000) than unrelated ones between 800 - 1000 ms, which might reflect a classification process preliminarily evaluating whether there were attainable cues in the pictures used to form possible association between context and picture (we named it “association evaluation” stage). Furthermore, humorous items elicited a more positive slow wave than non-humorous items which also elicited a more positive wave than unrelated items between 1000 - 1600 ms, during which this component might be involved in the forming of novel associations (resolution of incongruity). Lastly, between 1600 - 2000 ms, humorous items elicited a more positive ERP deflection (P1600-2000) than both non-humorous and unrelated items, which might be related to emotion processing during humor apprehension. Based on these results, we deeply subdivided the second stage (resolution of incongruity) into two stages: association evaluation and incongruity resolution.展开更多
Holography is an interesting tool in creating real objects and scenes which can be projected anywhere with accurate details and depth impression. It is also found to be more attractive to the artists than other altern...Holography is an interesting tool in creating real objects and scenes which can be projected anywhere with accurate details and depth impression. It is also found to be more attractive to the artists than other alternatives. For that reason, digital holography is being used as a display technology in cartoon movies. Since this application is dependent on the performance and the simplicity of the available display technology, it becomes very useful to improve the display technique in order to become fast, simple, and attractive by being combined with computer graphical effects. This paper discusses a simulation of a digital holographic model as a three dimensional (3D) display system and its application in making cartoon holography.展开更多
The present paper examines the vocabulary contained in the British animated programme Peppa Pig and investigates whether this vocabulary is highly frequent but also appropriate for beginner learners of English.It also...The present paper examines the vocabulary contained in the British animated programme Peppa Pig and investigates whether this vocabulary is highly frequent but also appropriate for beginner learners of English.It also examines if there is any formulaic language in it.Comparison with the BNC wordlist,the CYLET and EVP wordlists for beginners suggests that one fifth of the English vocabulary contained in the show is highly frequent and that a small amount of it overlaps with the proposed vocabulary lists of CYLET and EVP for A1 level.Therefore,the majority of the vocabulary contained in the show is mainly infrequent but still appropriate while the in-depth analysis of selective episodes showed amplitude of formulaic language in the show and plenty repetition of it.展开更多
Visual illustration transformation from real-world to cartoon images is one of the famous and challenging tasks in computer vision.Image-to-image translation from real-world to cartoon domains poses issues such as a l...Visual illustration transformation from real-world to cartoon images is one of the famous and challenging tasks in computer vision.Image-to-image translation from real-world to cartoon domains poses issues such as a lack of paired training samples,lack of good image translation,low feature extraction from the previous domain images,and lack of high-quality image translation from the traditional generator algorithms.To solve the above-mentioned issues,paired independent model,high-quality dataset,Bayesian-based feature extractor,and an improved generator must be proposed.In this study,we propose a high-quality dataset to reduce the effect of paired training samples on the model’s performance.We use a Bayesian Very Deep Convolutional Network(VGG)-based feature extractor to improve the performance of the standard feature extractor because Bayesian inference regu-larizes weights well.The generator from the Cartoon Generative Adversarial Network(GAN)is modified by introducing a depthwise convolution layer and channel attention mechanism to improve the performance of the original generator.We have used the Fréchet inception distance(FID)score and user preference score to evaluate the performance of the model.The FID scores obtained for the generated cartoon and real-world images are 107 and 76 for the TCC style,and 137 and 57 for the Hayao style,respectively.User preference score is also calculated to evaluate the quality of generated images and our proposed model acquired a high preference score compared to other models.We achieved stunning results in producing high-quality cartoon images,demonstrating the proposed model’s effectiveness in transferring style between authentic images and cartoon images.展开更多
文摘Do you like cartoons?I am crazy about cartoons because they are very interesting and cartoon music listens really great.I have a great time when I watch the cartoon films.
基金supported by the Wuhan University Undergraduate Project of Innovation and Entrepreneurship Training“The Evolution of Cartoon Images of Pandas in Western Media’s China-Related News From the Perspective of Multimodal Theory”(Project Number:S202410486013).
文摘Applying visual grammar theory,this study examines representational,interactive,and compositional meanings of the giant panda in Western media cartoons related to China from 1999 to the present.Distinct phases in the panda’s representation were identified and illustrated by cases of cartoons in major Western media.These phases trace shift of panda cartoon image from a symbol of peace and friendliness to a politicized emblem of China’s international stance.Key visual trends,such as transitivity,color symbolism,scale enlargement,and increasing compositional complexity,embody the panda’s role in shaping China’s global image and its function in international discourse.These trends reflect the panda’s transformation into a contested symbol,which mediates between China’s self-representation and Western perceptions of its geopolitical rise.By situating the analysis within the context of China’s growing global influence,this study contributes to visual and media studies,demonstrating how cultural symbols are recontextualized to reflect and shape geopolitical narratives.
文摘Automated cartoon character recognition is crucial for applications in content indexing,filtering,and copyright protection,yet it faces a significant challenge in animated media due to high intra-class visual variability,where characters frequently alter their appearance.To address this problem,we introduce the novel Kral Sakir dataset,a public benchmark of 16,725 images specifically curated for the task of multi-label cartoon character classification under these varied conditions.This paper conducts a comprehensive benchmark study,evaluating the performance of state-of-the-art pretrained Convolutional Neural Networks(CNNs),including DenseNet,ResNet,and VGG,against a custom baseline model trained from scratch.Our experiments,evaluated using metrics of F1-Score,accuracy,and Area Under the ROC Curve(AUC),demonstrate that fine-tuning pretrained models is a highly effective strategy.The best-performing model,DenseNet121,achieved an F1-Score of 0.9890 and an accuracy of 0.9898,significantly outperforming our baseline CNN(F1-Score of 0.9545).The findings validate the power of transfer learning for this domain and establish a strong performance benchmark.The introduced dataset provides a valuable resource for future research into developing robust and accurate character recognition systems.
基金supported by the New Talent Program of Zhejiang Province, China (2013R404046)
文摘Animation creates a vivid, virtual world and expands the scope of human imagination. In this study, we investigated the time-courses of brain responses related to the evaluation of the attractiveness of cartoon faces using the event-related potential （ERP） technique. The results demonstrated that N170 amplitude was higher for attractive than for unattractive cartoon faces in males, while the opposite was found in females. Facial attractiveness notably modulated the late positive component （LPC）, which might reflect the task-related process of aesthetic appraisal of beauty. The mean LPC amplitude in males was significantly higher for attractive cartoon faces than for unattractive faces, while the LPC amplitude in females did not significantly differ between attractive and unattractive cartoon faces. Moreover, the paint mode （computer graphics, gouache, and stick figure） modulated the early encoding of facial structures and the late evaluative process. The early modulation effect by paint mode may be related to the spatial frequency of the pictures. The processing speed and intensity in females were both higher than those in males. In conclusion, our study, for the first time, reported ERP modulation based on the assessment of cartoon facial attractiveness, suggesting the facilitated selection of attractiveness information at the early stage, and that the attentional enhancement of attractive faces at the late stage only exists in males. This suggests that men＇s brains are hard-wired to be sensitive to facial beauty, even in cartoons.
基金Supported by Hangzhou Medical and Health Technology Project,No.OO20191141。
文摘BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.
文摘The aim of this study was to investigate the temporal cortical activation patterns underlying different stages of humor comprehension (e.g., detection of incongruity stage, resolution of incongruity stage, and affective stage). Event-related potentials (ERPs) were measured when 16 subjects were apprehending cartoon pictures including humorous, non-humorous and unrelated items. Results showed that both humorous and unrelated items elicited a more negative ERP deflection (N500-800) than non-humorous ones between 500 - 800 ms, which might reflect detection to incongruent element during humor apprehension. Then, both humorous and non-humorous items elicited a more positive ERP deflection (P800-1000) than unrelated ones between 800 - 1000 ms, which might reflect a classification process preliminarily evaluating whether there were attainable cues in the pictures used to form possible association between context and picture (we named it “association evaluation” stage). Furthermore, humorous items elicited a more positive slow wave than non-humorous items which also elicited a more positive wave than unrelated items between 1000 - 1600 ms, during which this component might be involved in the forming of novel associations (resolution of incongruity). Lastly, between 1600 - 2000 ms, humorous items elicited a more positive ERP deflection (P1600-2000) than both non-humorous and unrelated items, which might be related to emotion processing during humor apprehension. Based on these results, we deeply subdivided the second stage (resolution of incongruity) into two stages: association evaluation and incongruity resolution.
文摘Holography is an interesting tool in creating real objects and scenes which can be projected anywhere with accurate details and depth impression. It is also found to be more attractive to the artists than other alternatives. For that reason, digital holography is being used as a display technology in cartoon movies. Since this application is dependent on the performance and the simplicity of the available display technology, it becomes very useful to improve the display technique in order to become fast, simple, and attractive by being combined with computer graphical effects. This paper discusses a simulation of a digital holographic model as a three dimensional (3D) display system and its application in making cartoon holography.
文摘The present paper examines the vocabulary contained in the British animated programme Peppa Pig and investigates whether this vocabulary is highly frequent but also appropriate for beginner learners of English.It also examines if there is any formulaic language in it.Comparison with the BNC wordlist,the CYLET and EVP wordlists for beginners suggests that one fifth of the English vocabulary contained in the show is highly frequent and that a small amount of it overlaps with the proposed vocabulary lists of CYLET and EVP for A1 level.Therefore,the majority of the vocabulary contained in the show is mainly infrequent but still appropriate while the in-depth analysis of selective episodes showed amplitude of formulaic language in the show and plenty repetition of it.
文摘Visual illustration transformation from real-world to cartoon images is one of the famous and challenging tasks in computer vision.Image-to-image translation from real-world to cartoon domains poses issues such as a lack of paired training samples,lack of good image translation,low feature extraction from the previous domain images,and lack of high-quality image translation from the traditional generator algorithms.To solve the above-mentioned issues,paired independent model,high-quality dataset,Bayesian-based feature extractor,and an improved generator must be proposed.In this study,we propose a high-quality dataset to reduce the effect of paired training samples on the model’s performance.We use a Bayesian Very Deep Convolutional Network(VGG)-based feature extractor to improve the performance of the standard feature extractor because Bayesian inference regu-larizes weights well.The generator from the Cartoon Generative Adversarial Network(GAN)is modified by introducing a depthwise convolution layer and channel attention mechanism to improve the performance of the original generator.We have used the Fréchet inception distance(FID)score and user preference score to evaluate the performance of the model.The FID scores obtained for the generated cartoon and real-world images are 107 and 76 for the TCC style,and 137 and 57 for the Hayao style,respectively.User preference score is also calculated to evaluate the quality of generated images and our proposed model acquired a high preference score compared to other models.We achieved stunning results in producing high-quality cartoon images,demonstrating the proposed model’s effectiveness in transferring style between authentic images and cartoon images.
