A smart waste classification model using hybrid CNN-LSTM with transfer learning for sustainable environment
… significantly improved image recognition and tracking [8]. … and b o represents a bias value
towards a forget Gate’s input and … management system that can efficiently classify garbage and …
towards a forget Gate’s input and … management system that can efficiently classify garbage and …
An internet of things based smart waste management system using LoRa and tensorflow deep learning model
… IoT application in the waste bin is one step towards a smart city. In addition, deep learning
… 95% test accuracy when done using transfer learning with defined weight. However, this …
… 95% test accuracy when done using transfer learning with defined weight. However, this …
Toward smarter management and recovery of municipal solid waste: A critical review on deep learning approaches
… of the most important models for image recognition and classification. Large … Transfer
learning, which is a specific branch of deep learning, aims to transfer knowledge to new systems …
learning, which is a specific branch of deep learning, aims to transfer knowledge to new systems …
[HTML][HTML] Intelligent waste management system using deep learning with IoT
… CNN presents tremendous progress in image recognition. In general, they are … The
corresponding result and data were sent via webserver towards an … A survey on transfer learning …
corresponding result and data were sent via webserver towards an … A survey on transfer learning …
A novel yolov3 algorithm-based deep learning approach for waste segregation: Towards smart waste management
… of a robust smart waste management system for proper waste segregation based on its …
to overfitting and to handle such a problem, a transfer learning approach is used [25]. In this …
to overfitting and to handle such a problem, a transfer learning approach is used [25]. In this …
Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
… Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit
… image recognition. Then a deep learning model pretrained on a visual recognition dataset is …
… image recognition. Then a deep learning model pretrained on a visual recognition dataset is …
[HTML][HTML] Next-generation energy systems for sustainable smart cities: Roles of transfer learning
… 3 - Transfer Learning (TL): if we consider a source domain D S and its corresponding task
T S , a learned function F S can be interpreted as the knowledge obtained in D S using T S . …
T S , a learned function F S can be interpreted as the knowledge obtained in D S using T S . …
Automatic detection and classification system of domestic waste via multimodel cascaded convolutional neural network
… We developed a smart trash bin (STC) system as the front-… learning approach for smart waste
management systems,” IEEE … using deep transfer learning,” IEEE Trans. Ind. Informat., vol. …
management systems,” IEEE … using deep transfer learning,” IEEE Trans. Ind. Informat., vol. …
Precision measurement for industry 4.0 standards towards solid waste classification through enhanced imaging sensors and deep learning model
… The study done by [31] leveraged the transfer learning using a pretrained network utilizing
AlexNet, GoogLeNet, VGG-16, and ResNet to classify waste images with different categories …
AlexNet, GoogLeNet, VGG-16, and ResNet to classify waste images with different categories …
Literature review on transfer learning for human activity recognition using mobile and wearable devices with environmental technology
… This literature review summarises the transfer learning techniques and explores … environmental
sensors in support of transfer learning. We also discuss the maturity of transfer learning …
sensors in support of transfer learning. We also discuss the maturity of transfer learning …