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Practical Steps For Literal Translation: گــام¬های عـملی یک ترجــمهء حرفه¬ای
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The present paper, practical methods of professional translation, discusses the most important methods to achieve an accurate effective translation from the source language text  to the equivalent target language text.

The present study suggests that practical translation like any literary activity is of six main stages that follow sequential order to achieve an accurate translation: (choosing the foreign text to be translated, the author of the text permission, the text translation, considering the title contextual meaning, reviewing the text translation, and finally finding a good publisher).

چکیده

پژوهش حاضر که با عنوان گام­های عملی یک ترجمهء حرفه­­­­­­­­ای يك تلاش فروتنانه به دنبال بررسی وتحلیل گام­های عملی ترجمه حرفه­ای است، كه هر مترجم برای ارائه یک ترجمه خوب و درست از زبان مبدأ به زبان مقصد باید ان را دنبال کند.

        پژوهش از شش مطلب تشکیل یافته است, كه مجموع آن گام­های عملی یک ترجمهء حرفه­ای به شمار می روند .از میان مهمترین نتایجی که پژوهشگر به آن رسیده: ترجمه هم مانند هر فعالیت ادبی باید طبق مرحله­هایی یا با گام­های مرتب ویکی پس از دیگری انجام شود وگرنه کار کم اهمیت خواهد بود, و گام­های عملی ترجمه حرفه­ای عبارتنداز: انتخاب کتاب،گرفتن اجازه از صاحب اثر،شروع به ترجمهء متن اثر،ترجمهء عنوان کتاب ، ویرایش وانتخاب ناشر.

 

 

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Tue Jul 13 2021
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