Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of re...Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of research.To perform the investigation on Plant and pest classification,Transfer Learning(TL)approach is used on EfficientNet-V2.TL requires limited labelled data and shorter training time.However,the limitation of TL is the pre-trained model network’s topology is static and the knowledge acquired is detrimentally overwriting the old parameters.EfficientNet-V2 is a Convolutional Neural Network(CNN)model with significant high speed learning rates across variable sized datasets.The model employs a form of progressive learning mechanism which expands the network topology gradually over the course of training process improving the model’s learning capacity.This provides a better interpretability of the model’s understanding on the test domains.With these insights,our work investigates the effectiveness of EfficienetV2 model trained on a class imbalanced dataset for plant disease classification and pest recognition by means of combining TL and progressive learning approach.This Progressive Learning for TL(PL-TL)is used in our work consisting of 38 classes of PlantVillage dataset of crops and fruit species,5 classes of cassava leaf diseases and another dataset with around 102 classes of crop pest images downloaded from popular dataset platforms,though it is not a benchmark dataset.To test the predictability rate of the model in classifying leaf diseases with similar visual symptoms,Mix-up data augmentation technique is used at the ratio of 1:4 on corn and tomato classes which has high probability of misinterpretation of disease classes.Also,the paper compares the TL approach performed on the above mentioned three types of data set using well established CNN based Inceptionv3,and Vision Transformer a non-CNN model.It clearly depicts that EfficientNetV2 has an outstanding performance of 99.5%,97.5%,80.1%on Cassava,PlantVillage and IP102 datasets respectively at a faster rate irrespective of the data size and class distribution as compared to Inception-V3 and ViT models.The performance metrics in terms of accuracy,precision,f1-score is also studied.展开更多
The Surface engineering of nanoparticles has contributed to the development of nanoscience and nanotechnology by designing of new material depends on their surface modifier with series of functional properties and app...The Surface engineering of nanoparticles has contributed to the development of nanoscience and nanotechnology by designing of new material depends on their surface modifier with series of functional properties and applications.The dispersed nanoparticles can change or modify the interfacial properties in liquid-liquid system in aqueous phase if their surface is modified by ionic surfactant.The interfacial energy in nanoparticles-brine system,the ions tends to modify the transport phenomena in pore channels and improve the recovery.The use of the suspension of the particles at nanoscales can offer some advantages of induced sedimentation stability by surface force easily counter balance the force of gravity.This happened due to their nanosize,nanostructure,high volume to surface ratio and strong rock fluid interaction.It also influences the emulsion stability and alters the surface characteristics of surfactant and polymer within the rock in porous medium.Some of the problems associated with conventional EOR processes have been solved by nanoscience applications due to their potential response to reduce the interfacial tension at low to ultra-low level,wettability reversal and improvement in rheology of formation fluids.The large specific surface area,high reactivity,toughness and other properties of Nanoparticles can immensely improve the oil mobility compare to conventional EOR.This paper updates the latest review,experimental evidences and re-interpretation of past research data and applications in respect of silica and titanium dioxide nanoparticles in different environment within surfactant(s),polymer(s),polymer-surfactant EOR processes.The nanotechnology therefore is an effective and alternate solution to brush up the traditional EOR approach with state of art technology which can revolutionize the total oil and gas industry and can contributes significantly to enhance the economics of oil field industry.展开更多
文摘Plant disease classification and prevention of spreading of the disease at earlier stages based on visual leaves symptoms and Pest recognition through deep learning-based image classification is in the forefront of research.To perform the investigation on Plant and pest classification,Transfer Learning(TL)approach is used on EfficientNet-V2.TL requires limited labelled data and shorter training time.However,the limitation of TL is the pre-trained model network’s topology is static and the knowledge acquired is detrimentally overwriting the old parameters.EfficientNet-V2 is a Convolutional Neural Network(CNN)model with significant high speed learning rates across variable sized datasets.The model employs a form of progressive learning mechanism which expands the network topology gradually over the course of training process improving the model’s learning capacity.This provides a better interpretability of the model’s understanding on the test domains.With these insights,our work investigates the effectiveness of EfficienetV2 model trained on a class imbalanced dataset for plant disease classification and pest recognition by means of combining TL and progressive learning approach.This Progressive Learning for TL(PL-TL)is used in our work consisting of 38 classes of PlantVillage dataset of crops and fruit species,5 classes of cassava leaf diseases and another dataset with around 102 classes of crop pest images downloaded from popular dataset platforms,though it is not a benchmark dataset.To test the predictability rate of the model in classifying leaf diseases with similar visual symptoms,Mix-up data augmentation technique is used at the ratio of 1:4 on corn and tomato classes which has high probability of misinterpretation of disease classes.Also,the paper compares the TL approach performed on the above mentioned three types of data set using well established CNN based Inceptionv3,and Vision Transformer a non-CNN model.It clearly depicts that EfficientNetV2 has an outstanding performance of 99.5%,97.5%,80.1%on Cassava,PlantVillage and IP102 datasets respectively at a faster rate irrespective of the data size and class distribution as compared to Inception-V3 and ViT models.The performance metrics in terms of accuracy,precision,f1-score is also studied.
文摘The Surface engineering of nanoparticles has contributed to the development of nanoscience and nanotechnology by designing of new material depends on their surface modifier with series of functional properties and applications.The dispersed nanoparticles can change or modify the interfacial properties in liquid-liquid system in aqueous phase if their surface is modified by ionic surfactant.The interfacial energy in nanoparticles-brine system,the ions tends to modify the transport phenomena in pore channels and improve the recovery.The use of the suspension of the particles at nanoscales can offer some advantages of induced sedimentation stability by surface force easily counter balance the force of gravity.This happened due to their nanosize,nanostructure,high volume to surface ratio and strong rock fluid interaction.It also influences the emulsion stability and alters the surface characteristics of surfactant and polymer within the rock in porous medium.Some of the problems associated with conventional EOR processes have been solved by nanoscience applications due to their potential response to reduce the interfacial tension at low to ultra-low level,wettability reversal and improvement in rheology of formation fluids.The large specific surface area,high reactivity,toughness and other properties of Nanoparticles can immensely improve the oil mobility compare to conventional EOR.This paper updates the latest review,experimental evidences and re-interpretation of past research data and applications in respect of silica and titanium dioxide nanoparticles in different environment within surfactant(s),polymer(s),polymer-surfactant EOR processes.The nanotechnology therefore is an effective and alternate solution to brush up the traditional EOR approach with state of art technology which can revolutionize the total oil and gas industry and can contributes significantly to enhance the economics of oil field industry.
