Results 201 to 210 of about 159,892 (265)

Nanomaterial Integration at Liquid–Liquid Interfaces for Green Catalysis

Advanced Materials, EarlyView.
Functional nanomaterials assembled at liquid–liquid interfaces create dual‐role platforms serving as emulsion stabilizers and catalytic sites, offering enhanced reaction kinetics with improved catalyst recovery and recyclability. This review examines design strategies, structure‐performance relationships, and industrial implementation prospects of ...
Bokgi Seo, Jaewon Shin, Minkyoung Jang, Kyoungho Choi, Tengfei Pang, Fangrui Zhong, Jin Woong Kim   +6 more
wiley   +1 more source

Deep Attention Fusion Hashing (DAFH) Model for Medical Image Retrieval. [PDF]

Bioengineering (Basel)
Wu G, Jin E, Sun Y, Tang B, Zhao W.
europepmc   +1 more source

Designable van der Waals Crystal for Artificial Neuronal Cell Mimicking

Advanced Materials, EarlyView.
Designable van der Waals crystal has been demonstrated for device‐scale neuronal cell mimicking. The structural similarity between ion‐channel in biological membranes and layered vdW lattices is realized with nano‐crystallization via Ar + H2S plasma sulfurization.
Jinhyoung Lee, Gunhyoung Kim, Dongho Lee, Seowoo Son, Hyunho Seok, Sihoon Son, Hyunbin Choi, Geonwook Kim, Geumji Back, Hyunkyu Kim, Chaerin Park, Junmin Ahn, Seongyun Je, Chaeyoung Im, Junil Cho, Magdalena Grzeszczyk, Seongho Kim, Eunseo Go, Hyunwoo Shim, Donghwan Choi, Muyoung Kim, Hyoeng‐U. Kim, Won‐Jun Jang, Taesung Kim   +23 more
wiley   +1 more source

DarwinGSE: Towards better image retrieval systems for intellectual property datasets. [PDF]

PLoS One
António J, Valente J, Mora C, Almeida A, Jardim S.   +4 more
europepmc   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

Advanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong, Xieyu Chen, Aarthy Nagarajan, Yi Yang, Zhihao Wang, Rui Yu, Chuang Zheng, Chunmei Ouyang, Xueqian Zhang, Tun Cao, Ranjan Singh, Zhen Tian   +11 more
wiley   +1 more source

Efficient Image Retrieval Using Hierarchical K-Means Clustering. [PDF]

Sensors (Basel)
Park D, Hwang Y.
europepmc   +1 more source

Benchmarking Deep Learning-Based Image Retrieval of Oral Tumor Histology. [PDF]

Cureus
Herdiantoputri RR, Komura D, Ochi M, Fukawa Y, Kayamori K, Tsuchiya M, Kikuchi Y, Ushiku T, Ikeda T, Ishikawa S.   +9 more
europepmc   +1 more source

Multi-FusNet: fusion mapping of features for fine-grained image retrieval networks. [PDF]

PeerJ Comput Sci
Cui X, Li H, Liu L, Wang S, Xu F.
europepmc   +1 more source

Enhancing Medical Image Retrieval with UMLS-Integrated CNN-Based Text Indexing. [PDF]

Diagnostics (Basel)
Gasmi K, Ayadi H, Torjmen M.
europepmc   +1 more source

Detection of Acromion Types in Shoulder Magnetic Resonance Image Examination with Developed Convolutional Neural Network and Textural-Based Content-Based Image Retrieval System. [PDF]

J Clin Med
Akçiçek M, Karaduman M, Petik B, Ünlü S, Mutlu HB, Yildirim M.   +5 more
europepmc   +1 more source