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All Journal Bulletin of Electrical Engineering and Informatics International Journal of Finance Research
Faruk, Md. Omar
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Economics, Econometrics & Finance Electrical & Electronics Engineering Social Sciences

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Bangla handwritten word recognition using YOLO V5 Hossain, Md. Anwar; Abadin, AFM Zainul; Faruk, Md. Omar; Ara, Iffat; Rashidul Hasan, Mirza AFM; Fatta, Nafiul; Asraful, Md; Hossen, Ebrahim
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6953

Abstract

This research paper presents an innovative solution for offline handwritten word recognition in Bengali, a prominent Indic language. The complexities of this script, particularly in cursive writing, often lead to overlapping characters and segmentation challenges. Conventional methodologies, reliant on individual character recognition and aggregation, are error-prone. To overcome these limitations, we propose a novel method treating the entire document as a coherent entity and utilizing the efficient you only look once (YOLO) model for word extraction. In our approach, we view individual words as distinct objects and employ the YOLO model for supervised learning, transforming object detection into a regression problematic to predict spatially detached bounding boxes and class possibilities. Rigorous training results in outstanding performance, with remarkable box_loss of 0.014, obj_loss of 0.14, and class_loss of 0.009. Furthermore, the achieved mAP_0.5 score of 0.95 and map_0.5:0.95 score of 0.97 demonstrates the model’s exceptional accuracy in detecting and recognizing handwritten words. To evaluate our method comprehensively, we introduce the Omor-Ekush dataset, a meticulously curated collection of 21,300 handwritten words from 150 participants, featuring 141 words per document. Our pioneering YOLO-based approach, combined with the curated Omor-Ekush dataset, represents a significant advancement in handwritten word recognition in Bengali.
Analysis on the Financial Performance of Selected Cement Industries of Bangladesh Ershad, Subarna; Uddin, Md. Minhaz; Faruk, Md. Omar
International Journal of Finance Research Vol. 2 No. 1 (2021): International Journal of Finance Research
Publisher : Training & Research Institute - Jeramba Ilmu Sukses (TRI-JIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/ijfr.v2i1.334

Abstract

This paper aims to analyze the financial performance of industries of Bangladesh, which are performing a crucial role in the current economic development trend of the country. Heidelberg Cement Bangladesh Ltd, Crown Cement, Lafarge Holcim and Meghna Cements are selected for analysis for their 70% of market share coverage of the cement industry. Competency of selected leading four cement companies are looked over here with some financial parameters like Return on Asset (ROA), Return on Equity (ROE), Earnings Per Share (EPS), Total Debt Ratio (TDR), Current Ratio (CR), Net Working Capital Ratio (NWCR), Assets Turnover Ratio (ATR) and mean value analysis technique. In preferred financial parameters and mean value analysis technique Heidelberg Cement Bangladesh Ltd has a good position, and in most cases, Meghna Cements obtained the lowest score. To attain desired efficacy in the cement industry of Bangladesh shortly, some prime recommendations such as reduction of production cost, prioritization on economies of scale, and business augmentation have come up here.
Co-Authors Abadin, AFM Zainul Ara, Iffat Asraful, Md Ershad, Subarna Fatta, Nafiul Hossain, Md. Anwar Hossen, Ebrahim Rashidul Hasan, Mirza AFM Uddin, Md. Minhaz