output
20082024
most citedSparseSwin: Swin Transformer with Sparse Transformer Block

48 citations

15 papers

eess.IV2024★ 4 cited

New Insight in Cervical Cancer Diagnosis Using Convolution Neural Network Architecture

Ach. Khozaimi, Wayan Firdaus Mahmudy

The Pap smear is a screening method for early cervical cancer diagnosis. The selection of the right optimizer in the convolutional neural network (CNN) model is key to the success…

cs.CV2024★ 1 cited

Hybrid of DiffStride and Spectral Pooling in Convolutional Neural Networks

Sulthan Rafif, Mochamad Arfan Ravy Wahyu Pratama, Mohammad Faris Azhar +3

Stride determines the distance between adjacent filter positions as the filter moves across the input. A fixed stride causes important information contained in the image can not be…

cs.LG2024★ 3 cited

Learning-Augmented K-Means Clustering Using Dimensional Reduction

Issam K. O Jabari, Shofiyah, Pradiptya Kahvi S +2

Learning augmented is a machine learning concept built to improve the performance of a method or model, such as enhancing its ability to predict and generalize data or features, or…

cs.AI2024

MAMI: Multi-Attentional Mutual-Information for Long Sequence Neuron Captioning

Alfirsa Damasyifa Fauzulhaq, Wahyu Parwitayasa, Joseph Ananda Sugihdharma +2

Neuron labeling is an approach to visualize the behaviour and respond of a certain neuron to a certain pattern that activates the neuron. Neuron labeling extract information about…

cs.CV2023★ 48 cited

SparseSwin: Swin Transformer with Sparse Transformer Block

Krisna Pinasthika, Blessius Sheldo Putra Laksono, Riyandi Banovbi Putera Irsal +2

Advancements in computer vision research have put transformer architecture as the state of the art in computer vision tasks. One of the known drawbacks of the transformer architect…

cs.CL2021★ 6 cited

Large-Scale News Classification using BERT Language Model: Spark NLP Approach

Kuncahyo Setyo Nugroho, Anantha Yullian Sukmadewa, Novanto Yudistira

The rise of big data analytics on top of NLP increases the computational burden for text processing at scale. The problems faced in NLP are very high dimensional text, so it takes…