How good are low-bit quantized llama3 models? an empirical study
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 …
Model (LLM) series. Notably, LLaMA3 models have recently been released and achieve …
An empirical study of llama3 quantization: From llms to mllms
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 …
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
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 …
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
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 …
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
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 …
users and connected devices. With the increasingly different types of malware released by …
A Simple Low-bit Quantization Framework for Video Snapshot Compressive Imaging
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 …
capture high-speed scene as snapshot compressed measurements, followed by a …
[HTML][HTML] A Comprehensive Survey of Deep Learning Approaches in Image Processing
The integration of deep learning (DL) into image processing has driven transformative
advancements, enabling capabilities far beyond the reach of traditional methodologies. This …
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 …
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 …
damaged road markings, this study proposes a Multi-level Adaptive Lightweight Network …
Rethinking Imbalance in Image Super-Resolution for Efficient Inference
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 …
{L} _1 $ or $\mathcal {L} _2 $ losses by uniformly sampling image patches without …