Research progress in fault detection of battery systems: a review
Numerous explorations have been made with the goal of achieving “carbon neutrality.”
Among them, lithium-ion batteries are an effective and efficient way to achieve this goal …
Among them, lithium-ion batteries are an effective and efficient way to achieve this goal …
Elucidating the design space of diffusion-based generative models
We argue that the theory and practice of diffusion-based generative models are currently
unnecessarily convoluted and seek to remedy the situation by presenting a design space …
unnecessarily convoluted and seek to remedy the situation by presenting a design space …
A review of convolutional neural networks in computer vision
In computer vision, a series of exemplary advances have been made in several areas
involving image classification, semantic segmentation, object detection, and image super …
involving image classification, semantic segmentation, object detection, and image super …
Characterizing signal propagation to close the performance gap in unnormalized resnets
Batch Normalization is a key component in almost all state-of-the-art image classifiers, but it
also introduces practical challenges: it breaks the independence between training examples …
also introduces practical challenges: it breaks the independence between training examples …
Compute-efficient deep learning: Algorithmic trends and opportunities
Although deep learning has made great progress in recent years, the exploding economic
and environmental costs of training neural networks are becoming unsustainable. To …
and environmental costs of training neural networks are becoming unsustainable. To …
TeutongNet: A fine-tuned deep learning model for improved forest fire detection
Forest fires have emerged as a significant threat to the environment, wildlife, and human
lives, necessitating the development of effective early detection systems for firefighting and …
lives, necessitating the development of effective early detection systems for firefighting and …
Shelving, stacking, hanging: Relational pose diffusion for multi-modal rearrangement
We propose a system for rearranging objects in a scene to achieve a desired object-scene
placing relationship, such as a book inserted in an open slot of a bookshelf. The pipeline …
placing relationship, such as a book inserted in an open slot of a bookshelf. The pipeline …
DNN model development of biogas production from an anaerobic wastewater treatment plant using Bayesian hyperparameter optimization
Deep neural networks have been regarded as accurate models to predict complex
fermentation processes due to their capacity to learn from a high number of data sets via …
fermentation processes due to their capacity to learn from a high number of data sets via …
Representative batch normalization with feature calibration
Abstract Batch Normalization (BatchNorm) has become the default component in modern
neural networks to stabilize training. In BatchNorm, centering and scaling operations, along …
neural networks to stabilize training. In BatchNorm, centering and scaling operations, along …
Multi-target backdoor attacks for code pre-trained models
Backdoor attacks for neural code models have gained considerable attention due to the
advancement of code intelligence. However, most existing works insert triggers into task …
advancement of code intelligence. However, most existing works insert triggers into task …