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Article
Computer Science, Interdisciplinary Applications
Yi Lin et al.
Summary: This study develops an acne diagnosis system that can be applied to different acne grading criteria. It imitates the dermatologist's diagnosis process by utilizing image preprocessing methods and network structures, achieving a diagnostic level comparable to professional dermatologists.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
Jose Ariel Camacho-Gutierrez et al.
Summary: Technological advances have provided specialists with a wide range of computer-aided diagnostic applications, but challenges remain in automating the classification of skin lesions. The study proposed new fractal signatures to address issues such as amorphous pigmentation and fuzzy edges. By using the ISIC database, the methodology was evaluated for multi-class classification of skin lesions.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Dermatology
Andrew Creadore et al.
Summary: The study found that patients with Medicaid had lower appointment success rates and longer wait times regardless of clinic ownership. Although the use of dermatologists and nonphysician clinicians was similar regardless of clinic ownership, PE-owned clinics were more likely to offer new patient appointments with nonphysician clinicians.
Article
Computer Science, Artificial Intelligence
Cheng Dai et al.
Summary: Knowledge distillation (KD) has been widely studied in recent deep learning research, but its effectiveness is compromised when there is a significant gap in strength between the teacher and student networks. To address this issue, the TDKD method is proposed to transfer complex mappings from cumbersome models to simpler ones by reducing capacity variance. This approach has been shown to effectively improve distillation performance and reactivate previously ineffective KD methods.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Saite Fan et al.
Summary: This paper introduces a reinforced knowledge distillation method to address the problem of multi-class imbalanced classification, utilizing an improved classification architecture and policy reinforcement learning. The approach incorporates a newly designed reward signal and sample weight update strategy, demonstrating good performance in experiments.
Article
Computer Science, Artificial Intelligence
Baiyun Cui et al.
Summary: This paper introduces a novel Joint Model Compression method that combines structured pruning and dense knowledge distillation techniques to compress large language models while maintaining accuracy. The proposed approach demonstrates significant effectiveness and superiority in various NLP tasks, with added benefits of improved inference-time speedup and memory efficiency.
Article
Computer Science, Artificial Intelligence
Abdolmaged Alkhulaifi et al.
Summary: This paper presents an outlook on knowledge distillation techniques applied to deep learning models, introducing a new metric called distillation metric for comparing performances of different solutions. Interesting conclusions drawn from the survey, along with current challenges and possible research directions, are discussed in the paper.
PEERJ COMPUTER SCIENCE
(2021)
Article
Computer Science, Theory & Methods
Cody Blakeney et al.
Summary: The article introduces a parallel blockwise distillation algorithm to accelerate the distillation process of complex DNNs. Experimental results show that the algorithm achieves 3x speedup and 19% energy savings in VGG distillation, and 3.5x speedup and 29% energy savings in ResNet distillation, with negligible accuracy loss. The speedup of ResNet distillation can be further improved to 3.87 when using four RTX6000 GPUs in a distributed cluster.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Shipeng Fu et al.
Summary: Knowledge distillation is a standard framework to train a light-weight student network under the guidance of a large teacher network, while Interactive Knowledge Distillation leverages interactive teaching strategy for efficient knowledge distillation. By implementing interaction through swapping operations between teacher and student networks, IAKD boosts student network performance by utilizing the powerful feature transformation ability of the teacher.
Article
Dermatology
Ziying Vanessa Lim et al.
SKIN RESEARCH AND TECHNOLOGY
(2020)
Article
Computer Science, Artificial Intelligence
Nazia Hameed et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Ghasem Shakourian Ghalejoogh et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Jie Hu et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2020)
Article
Dermatology
Sophie Seite et al.
EXPERIMENTAL DERMATOLOGY
(2019)
Article
Medicine, General & Internal
Hywel C. Williams et al.
Review
Dermatology
Roshaslinie Ramli et al.
SKIN RESEARCH AND TECHNOLOGY
(2012)
Article
Dermatology
S. Zahra Ghodsi et al.
JOURNAL OF INVESTIGATIVE DERMATOLOGY
(2009)
Article
Dermatology
JA Witkowski et al.
CLINICS IN DERMATOLOGY
(2004)
Article
Dermatology
B Dreno et al.
