3 papers
cs.LG2025
AdapSNE: Adaptive Fireworks-Optimized and Entropy-Guided Dataset Sampling for Edge DNN Training
Boran Zhao, Hetian Liu, Zihang Yuan +5
Training deep neural networks (DNNs) directly on edge devices has attracted increasing attention, as it offers promising solutions to challenges such as domain adaptation and priva…
cs.CV2024
MobileNetV4 -- Universal Models for the Mobile Ecosystem
Danfeng Qin, Chas Leichner, Manolis Delakis +11
We present the latest generation of MobileNets, known as MobileNetV4 (MNv4), featuring universally efficient architecture designs for mobile devices. At its core, we introduce the…
cs.CV2023
MaskConver: Revisiting Pure Convolution Model for Panoptic Segmentation
Abdullah Rashwan, Jiageng Zhang, Ali Taalimi +5
In recent years, transformer-based models have dominated panoptic segmentation, thanks to their strong modeling capabilities and their unified representation for both semantic and…