48 citations · 156 across the 30 of their papers we have counts for
30 papers
Zero-Shot Captioning for Cultural Heritage: Automated Image Analysis of Traditional Indonesian Clothing
Anugrah Aidin Yotolembah, Novanto Yudistira, Gembong Edhi Setyawan
This paper presents Custom ZeroCLIP, a retrieval-augmented vision-language framework for zero-shot captioning of Indonesian traditional garments. The dataset contains 3,800 expert-…
Does Language Shift Break Medical Vision-Language Models? Indonesian Radiology Visual Question Answering Case Study
Pieter Christy Yan Yudhistira, Dzaki Rafif Malik, Novanto Yudistira
Medical Vision-Language Models (VLMs) are typically evaluated on English radiology visual question answering benchmarks, leaving their robustness under non-English clinical languag…
Adaptive Conformal Prediction for Reliable and Explainable Medical Image Classification
One Octadion, Novanto Yudistira, Lailil Muflikhah
Deep learning models for medical imaging often exhibit overconfidence, creating safety risks in ambiguous diagnostic scenarios. While Conformal Prediction (CP) provides distributio…
Training-Free Disentangled Text-Guided Image Editing via Sparse Latent Constraints
Mutiara Shabrina, Nova Kurnia Putri, Jefri Satria Ferdiansyah +2
Text-driven image manipulation often suffers from attribute entanglement, where modifying a target attribute (e.g., adding bangs) unintentionally alters other semantic properties s…
Input-Adaptive Visual Preprocessing for Efficient Fast Vision-Language Model Inference
Putu Indah Githa Cahyani, Komang David Dananjaya Suartana, Novanto Yudistira
Vision-Language Models (VLMs) have demonstrated strong performance on multimodal reasoning tasks, but their deployment remains challenging due to high inference latency and computa…
Towards Adaptive Fusion of Multimodal Deep Networks for Human Action Recognition
Novanto Yudistira
This study introduces a pioneering methodology for human action recognition by harnessing deep neural network techniques and adaptive fusion strategies across multiple modalities,…
ASVRI-Legal: Fine-Tuning LLMs with Retrieval Augmented Generation for Enhanced Legal Regulation
One Octadion, Bondan Sapta Prakoso, Nanang Yudi Setiawan +1
In this study, we explore the fine-tuning of Large Language Models (LLMs) to better support policymakers in their crucial work of understanding, analyzing, and crafting legal regul…
Efficient Object Detection of Marine Debris using Pruned YOLO Model
Abi Aryaza, Novanto Yudistira, Tibyani
Marine debris poses significant harm to marine life due to substances like microplastics, polychlorinated biphenyls, and pesticides, which damage habitats and poison organisms. Hum…
Variational Mode Decomposition and Linear Embeddings are What You Need For Time-Series Forecasting
Hafizh Raihan Kurnia Putra, Novanto Yudistira, Tirana Noor Fatyanosa
Time-series forecasting often faces challenges due to data volatility, which can lead to inaccurate predictions. Variational Mode Decomposition (VMD) has emerged as a promising tec…
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…
IndoHerb: Indonesia Medicinal Plants Recognition using Transfer Learning and Deep Learning
Muhammad Salman Ikrar Musyaffa, Novanto Yudistira, Muhammad Arif Rahman +1
The rich diversity of herbal plants in Indonesia holds immense potential as alternative resources for traditional healing and ethnobotanical practices. However, the dwindling recog…
Mixture of Self-Supervised Learning
Aristo Renaldo Ruslim, Novanto Yudistira, Budi Darma Setiawan
Self-supervised learning is popular method because of its ability to learn features in images without using its labels and is able to overcome limited labeled datasets used in supe…
Sparse then Prune: Toward Efficient Vision Transformers
Yogi Prasetyo, Novanto Yudistira, Agus Wahyu Widodo
The Vision Transformer architecture is a deep learning model inspired by the success of the Transformer model in Natural Language Processing. However, the self-attention mechanism,…
Supervised Virtual-to-Real Domain Adaptation for Object Detection Task using YOLO
Akbar Satya Nugraha, Yudistira Novanto, Bayu Rahayudi
Deep neural network shows excellent use in a lot of real-world tasks. One of the deep learning tasks is object detection. Well-annotated datasets will affect deep neural network ac…
Text recognition on images using pre-trained CNN
Afgani Fajar Rizky, Novanto Yudistira, Edy Santoso
A text on an image often stores important information and directly carries high level semantics, makes it as important source of information and become a very active research topic…
Prediction of COVID-19 by Its Variants using Multivariate Data-driven Deep Learning Models
Akhmad Dimitri Baihaqi, Novanto Yudistira, Edy Santoso
The Coronavirus Disease 2019 or the COVID-19 pandemic has swept almost all parts of the world since the first case was found in Wuhan, China, in December 2019. With the increasing…
Gated Self-supervised Learning For Improving Supervised Learning
Erland Hilman Fuadi, Aristo Renaldo Ruslim, Putu Wahyu Kusuma Wardhana +1
In past research on self-supervised learning for image classification, the use of rotation as an augmentation has been common. However, relying solely on rotation as a self-supervi…
Deep Transformer Model with Pre-Layer Normalization for COVID-19 Growth Prediction
Rizki Ramadhan Fitra, Novanto Yudistira, Wayan Firdaus Mahmudy
Coronavirus disease or COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. The first confirmed case caused by this virus was found at the end of December 2019 in Wuha…
Classification of Alzheimer's Disease Using the Convolutional Neural Network (CNN) with Transfer Learning and Weighted Loss
Muhammad Wildan Oktavian, Novanto Yudistira, Achmad Ridok
Alzheimer's disease is a progressive neurodegenerative disorder that gradually deprives the patient of cognitive function and can end in death. With the advancement of technology t…
Image Colorization using U-Net with Skip Connections and Fusion Layer on Landscape Images
Muhammad Hisyam Zayd, Novanto Yudistira, Randy Cahya Wihandika
We present a novel technique to automatically colorize grayscale images that combine the U-Net model and Fusion Layer features. This approach allows the model to learn the coloriza…
Mask Usage Recognition using Vision Transformer with Transfer Learning and Data Augmentation
Hensel Donato Jahja, Novanto Yudistira, Sutrisno
The COVID-19 pandemic has disrupted various levels of society. The use of masks is essential in preventing the spread of COVID-19 by identifying an image of a person using a mask.…
Attention-effective multiple instance learning on weakly stem cell colony segmentation
Novanto Yudistira, Muthu Subash Kavitha, Jeny Rajan +1
The detection of induced pluripotent stem cell (iPSC) colonies often needs the precise extraction of the colony features. However, existing computerized systems relied on segmentat…
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…
BERT Fine-Tuning for Sentiment Analysis on Indonesian Mobile Apps Reviews
Kuncahyo Setyo Nugroho, Anantha Yullian Sukmadewa, Haftittah Wuswilahaken DW +2
User reviews have an essential role in the success of the developed mobile apps. User reviews in the textual form are unstructured data, creating a very high complexity when proces…