Comparison of vision transformers and convolutional neural networks in medical image analysis: a systematic review
S Takahashi, Y Sakaguchi, N Kouno… - Journal of Medical …, 2024 - Springer
In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the
selection of appropriate computational models is critical for accurate diagnosis and patient …
selection of appropriate computational models is critical for accurate diagnosis and patient …
Efficientformer: Vision transformers at mobilenet speed
Abstract Vision Transformers (ViT) have shown rapid progress in computer vision tasks,
achieving promising results on various benchmarks. However, due to the massive number of …
achieving promising results on various benchmarks. However, due to the massive number of …
A comprehensive review and a taxonomy of edge machine learning: Requirements, paradigms, and techniques
The union of Edge Computing (EC) and Artificial Intelligence (AI) has brought forward the
Edge AI concept to provide intelligent solutions close to the end-user environment, for …
Edge AI concept to provide intelligent solutions close to the end-user environment, for …
A survey of resource-efficient llm and multimodal foundation models
Large foundation models, including large language models (LLMs), vision transformers
(ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine …
(ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine …
Elasticvit: Conflict-aware supernet training for deploying fast vision transformer on diverse mobile devices
Abstract Neural Architecture Search (NAS) has shown promising performance in the
automatic design of vision transformers (ViT) exceeding 1G FLOPs. However, designing …
automatic design of vision transformers (ViT) exceeding 1G FLOPs. However, designing …
Advancements in accelerating deep neural network inference on aiot devices: A survey
The amalgamation of artificial intelligence with Internet of Things (AIoT) devices have seen a
rapid surge in growth, largely due to the effective implementation of deep neural network …
rapid surge in growth, largely due to the effective implementation of deep neural network …
Mobilediffusion: Subsecond text-to-image generation on mobile devices
The deployment of large-scale text-to-image diffusion models on mobile devices is impeded
by their substantial model size and slow inference speed. In this paper, we propose\textbf …
by their substantial model size and slow inference speed. In this paper, we propose\textbf …
RGB no more: Minimally-decoded JPEG Vision Transformers
Most neural networks for computer vision are designed to infer using RGB images. However,
these RGB images are commonly encoded in JPEG before saving to disk; decoding them …
these RGB images are commonly encoded in JPEG before saving to disk; decoding them …
[PDF][PDF] Resource-efficient algorithms and systems of foundation models: A survey
In the rapidly evolving field of artificial intelligence (AI), a paradigm shift is underway. We are
witnessing the transition from specialized, fragmented deep learning models to versatile …
witnessing the transition from specialized, fragmented deep learning models to versatile …
Learned thresholds token merging and pruning for vision transformers
M Bonnaerens, J Dambre - arXiv preprint arXiv:2307.10780, 2023 - arxiv.org
Vision transformers have demonstrated remarkable success in a wide range of computer
vision tasks over the last years. However, their high computational costs remain a significant …
vision tasks over the last years. However, their high computational costs remain a significant …