15 citations · 22 across the 5 of their papers we have counts for
6 papers
Class-Grounded Batik Captioning under Scarce Text Annotation: Label Retention and Source-Specific Error Propagation
Novanto Yudistira, Muhammad Dzaka Aufa Fadhillah, Irawati Nurmala Sari
Class labels offer compact supervision for describing cultural-heritage images when expert text annotations are scarce. We investigate a batik-captioning cascade that integrates a…
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…
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…
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…
Synthesis of Batik Motifs using a Diffusion -- Generative Adversarial Network
One Octadion, Novanto Yudistira, Diva Kurnianingtyas
Batik, a unique blend of art and craftsmanship, is a distinct artistic and technological creation for Indonesian society. Research on batik motifs is primarily focused on classific…
Weakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN
Novanto Yudistira, Muthu Subash Kavitha, Takio Kurita
3D Convolutional Neural Network (3D CNN) captures spatial and temporal information on 3D data such as video sequences. However, due to the convolution and pooling mechanism, the in…