activity
20192023
most citedThe SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methods

29 citations · 75 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2023★ 6 cited

IncreLoRA: Incremental Parameter Allocation Method for Parameter-Efficient Fine-tuning

Feiyu Zhang, Liangzhi Li, Junhao Chen +3

With the increasing size of pre-trained language models (PLMs), fine-tuning all the parameters in the model is not efficient, especially when there are a large number of downstream…

cs.CL2023★ 4 cited

CARE-MI: Chinese Benchmark for Misinformation Evaluation in Maternity and Infant Care

Tong Xiang, Liangzhi Li, Wangyue Li +4

The recent advances in natural language processing (NLP), have led to a new trend of applying large language models (LLMs) to real-world scenarios. While the latest LLMs are astoni…

cs.CV2023

Learning Bottleneck Concepts in Image Classification

Bowen Wang, Liangzhi Li, Yuta Nakashima +1

Interpreting and explaining the behavior of deep neural networks is critical for many tasks. Explainable AI provides a way to address this challenge, mostly by providing per-pixel…

cs.CV2021★ 29 cited

The SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methods

Vivek Singh Bawa, Gurkirt Singh, Francis KapingA +16

For an autonomous robotic system, monitoring surgeon actions and assisting the main surgeon during a procedure can be very challenging. The challenges come from the peculiar struct…

cs.CV2020★ 1 cited

Match Them Up: Visually Explainable Few-shot Image Classification

Bowen Wang, Liangzhi Li, Manisha Verma +3

Few-shot learning (FSL) approaches are usually based on an assumption that the pre-trained knowledge can be obtained from base (seen) categories and can be well transferred to nove…

eess.IV2020

Automated Grading System of Retinal Arterio-venous Crossing Patterns: A Deep Learning Approach Replicating Ophthalmologist's Diagnostic Process of Arteriolosclerosis

Liangzhi Li, Manisha Verma, Bowen Wang +3

The status of retinal arteriovenous crossing is of great significance for clinical evaluation of arteriolosclerosis and systemic hypertension. As an ophthalmology diagnostic criter…

cs.CV2020

Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation

Bowen Wang, Liangzhi Li, Yuta Nakashima +3

Semantic video segmentation is a key challenge for various applications. This paper presents a new model named Noisy-LSTM, which is trainable in an end-to-end manner, with convolut…

cs.CV2020

SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition

Liangzhi Li, Bowen Wang, Manisha Verma +3

Explainable artificial intelligence has been gaining attention in the past few years. However, most existing methods are based on gradients or intermediate features, which are not…

cs.CV2020★ 13 cited

Joint Learning of Vessel Segmentation and Artery/Vein Classification with Post-processing

Liangzhi Li, Manisha Verma, Yuta Nakashima +2

Retinal imaging serves as a valuable tool for diagnosis of various diseases. However, reading retinal images is a difficult and time-consuming task even for experienced specialists…

eess.IV2019★ 22 cited

IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks

Liangzhi Li, Manisha Verma, Yuta Nakashima +2

Retinal vessel segmentation is of great interest for diagnosis of retinal vascular diseases. To further improve the performance of vessel segmentation, we propose IterNet, a new mo…