How good are low-bit quantized llama3 models? an empirical study

W Huang, X Ma, H Qin, X Zheng, C Lv, H Chen… - arxiv e …, 2024 - ui.adsabs.harvard.edu
Meta's LLaMA family has become one of the most powerful open-source Large Language
Model (LLM) series. Notably, LLaMA3 models have recently been released and achieve …

An empirical study of llama3 quantization: From llms to mllms

W Huang, X Zheng, X Ma, H Qin, C Lv, H Chen, J Luo… - Visual Intelligence, 2024 - Springer
The LLaMA family, a collection of foundation language models ranging from 7B to 65B
parameters, has become one of the most powerful open-source large language models …

[HTML][HTML] Enhancing brain tumor segmentation in MRI images: A hybrid approach using UNet, attention mechanisms, and transformers

TB Nguyen-Tat, TQT Nguyen, HN Nguyen… - Egyptian Informatics …, 2024 - Elsevier
Accurate brain tumor segmentation in MRI images is crucial for effective treatment planning
and monitoring. Traditional methods often encounter challenges due to the complexity and …

[HTML][HTML] Multilevel thresholding Aerial image segmentation using comprehensive learning-based Snow ablation optimizer with double attractors

M Abd Elaziz, MAA Al-qaness, RA Ibrahim… - Egyptian Informatics …, 2024 - Elsevier
Aerial photography is a remote sensing technique used for target detection, enabling both
qualitative and quantitative analysis. The segmentation process is considered one of the …

[HTML][HTML] Deep hybrid approach with sequential feature extraction and classification for robust malware detection

S Singh, D Krishnan, V Vazirani, V Ravi… - Egyptian Informatics …, 2024 - Elsevier
Malware attacks have escalated significantly with an increase in the number of internet
users and connected devices. With the increasingly different types of malware released by …

A Simple Low-bit Quantization Framework for Video Snapshot Compressive Imaging

M Cao, L Wang, H Wang, X Yuan - European Conference on Computer …, 2024 - Springer
Abstract Video Snapshot Compressive Imaging (SCI) aims to use a low-speed 2D camera to
capture high-speed scene as snapshot compressed measurements, followed by a …

[HTML][HTML] A Comprehensive Survey of Deep Learning Approaches in Image Processing

M Trigka, E Dritsas - Sensors, 2025 - mdpi.com
The integration of deep learning (DL) into image processing has driven transformative
advancements, enabling capabilities far beyond the reach of traditional methodologies. This …

Application of human posture recognition and classification in performing arts education

J Shen, L Chen - IEEE Access, 2024 - ieeexplore.ieee.org
This review explores the integration of human posture recognition and classification
technologies in performing arts education, focusing on the advancements in deep learning …

[HTML][HTML] A Multi-Level Adaptive Lightweight Net for Damaged Road Marking Detection Based on Knowledge Distillation

J Wang, X Zeng, Y Wang, X Ren, D Wang, W Qu… - Remote Sensing, 2024 - mdpi.com
To tackle the complexity and limited applicability of high-precision segmentation models for
damaged road markings, this study proposes a Multi-level Adaptive Lightweight Network …

Rethinking Imbalance in Image Super-Resolution for Efficient Inference

W Yu, B Yang, L Qinglin, J Li… - Advances in Neural …, 2025 - proceedings.neurips.cc
Existing super-resolution (SR) methods optimize all model weights equally using $\mathcal
{L} _1 $ or $\mathcal {L} _2 $ losses by uniformly sampling image patches without …