Autodesk 3ds Max 2022 Crack + Product Key Free Download
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3d Max 64 Bit Download Crack
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Autodesk provides download and install instructions for individuals and administrators. Your available downloads appear in Autodesk Account or education site. Find your product, select a version, platform, language, and download method. For more information, visit the Autodesk Knowledge Network.\n"}]},"@type":"Question","name":"How long is the 3ds Max free trial?","acceptedAnswer":["@type":"Answer","text":"Trial versions of Autodesk software offer the chance to explore the full capabilities of the latest versions for a limited term (typically 30 days). To cancel a free trial, turn off automatic renewal before the trial period ends. If you were not required to enter a payment method at the start of the trial, it will expire automatically.\r\n"],"@type":"Question","name":"How do I extend the 3ds Max free trial?","acceptedAnswer":["@type":"Answer","text":"If your trial expires, you cannot extend the trial period. For short-term needs, you can purchase a monthly subscription and turn off automatic renewal (to limit the length of the paid subscription to one month only) or purchase Flex tokens for a flexible pay-as-you-go plan.\r\n"],"@type":"Question","name":"How do I troubleshoot 3ds Max download issues?","acceptedAnswer":["@type":"Answer","text":"If your installation or product download fails, try using the Browser Download method instead (not available in macOS). We recommend disabling pop-up blockers and trying a different browser, such as Chrome or Explorer. For more solutions, check out our guide to troubleshooting Autodesk product download issues.\r\n"],"@type":"Question","name":"Where do I download free 3ds Max software for students?","acceptedAnswer":["@type":"Answer","text":"Students and educators can get free one-year educational access to Autodesk products and services, renewable as long as you remain eligible. If you are a student or educator, you can access free 3ds Max software with an Autodesk Education plan.\r\n"],"@type":"Question","name":"How do I convert my 3ds Max free trial to a paid subscription?","acceptedAnswer":["@type":"Answer","text":"Launch your trial software and click Subscribe Now on the trial screen or visit the 3ds Max product center. When buying your subscription, enter the same email address and password combination you used to sign in to your trial. Learn more about converting a trial to a paid subscription.\r\n"]],"@type":"FAQPage","@context":" "} Autodesk Company overview Careers Investor relations Newsroom Diversity and belonging
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Autodesk provides download and install instructions for individuals and administrators. Your available downloads appear in Autodesk Account. Find your product, select a version, platform, language, and download method. For more information, visit the Autodesk Knowledge Network.
3ds Max is used to model, animate, and render detailed 3D characters, photorealistic designs, and complex scenes for film and TV, games, and design visualization projects.\r\n"}]},"@type":"Question","name":"Who uses 3ds Max?","acceptedAnswer":["@type":"Answer","text":"3ds Max is used by 3D modelers, animators, and lighting artists for game development, film and TV productions, and design visualization projects.\r\n"],"@type":"Question","name":"3ds Max vs Maya","acceptedAnswer":["@type":"Answer","text":"3ds Max and Maya are used by creative studios around the world for animation, modeling, visual effects, and rendering. Learn when to choose 3ds Max and when to choose Maya.\n"],"@type":"Question","name":"How do I download 3ds Max?","acceptedAnswer":["@type":"Answer","text":"Autodesk provides download and install instructions for individuals and administrators. Your available downloads appear in Autodesk Account. Find your product, select a version, platform, language, and download method. For more information, visit the Autodesk Knowledge Network.\n"],"@type":"Question","name":"Can I install 3ds Max on multiple computers?","acceptedAnswer":["@type":"Answer","text":"With a subscription to 3ds Max software, you can install it on up to 3 computers or other devices. However, only the named user can sign in and use that software on a single computer at any given time. Please refer to the\u202fSoftware License Agreement for more information.\r\n"],"@type":"Question","name":"How do I convert my 3ds Max free trial to a paid subscription?","acceptedAnswer":["@type":"Answer","text":"Launch your trial software and click Subscribe Now on the trial screen or buy 3ds Max here. When buying your subscription, enter the same email address and password combination you used to sign in to your trial. Learn more about\u202fconverting a trial to a paid subscription.\r\n"],"@type":"Question","name":"How much does a 3ds Max subscription cost?","acceptedAnswer":["@type":"Answer","text":"The price of an annual 3ds Max subscription is\u202f\u202fand the price of a monthly 3ds Max subscription is\u202f. The price of a 3-year 3ds Max subscription is\u202f. If you have infrequent users and are interested in a pay-as-you-go option, please visit www.autodesk.com/flex to learn more.\r\n"]],"@type":"FAQPage","@context":" "} Autodesk Company overview Careers Investor relations Newsroom Diversity and belonging
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Automatic crack detection is always a challenging task due to the influence of stains, shadows, complex texture, uneven illumination, blurring, and multiple scenes [2]. In the past decades, scholars have proposed a variety of image-based algorithms to automatically detect cracks on concrete surfaces and pavement. In the early studies, most of the methods are based on the combination or improvement of traditional digital image processing techniques (IPTs) [3], such as thresholding [4,5,6] and edge detection [7,8,9,10]. However, these methods are generally based on the significant assumption that the intensities of crack pixels are darker than the background and usually continuous, which makes these methods difficult to use effectively in the environment of complex background noise [11,12]. In order to improve the accuracy and integrity of crack detection, the methods based on wavelet transform [13,14] are proposed to lift the crack regions. However, due to the anisotropic characteristics of wavelets, they may not deal well with cracks with large curvatures or poor continuities [2].
In recent studies, several minimal path methods [15,16] have also been used for crack detection. Although these methods make use of crack features in a global view [3] and achieve good performance, their main limitation is that seed points for path tracking need to be set in advance [17], and the calculation cost is too high for practical application.
Unet [32], as a typical representative of semantic segmentation algorithm, has achieved great success in medical image segmentation. There are many similarities between pavement crack detection and medical image segmentation, so it is natural to apply Unet to pavement crack segmentation.
The patchwise detection method, which divides the original pavement images into many small patches, is adopted by more researchers due to its two advantages. First, more data can be generated, and second, the localization information of cracks can be obtained. Zhang et al. [39] proposed a six-layer CNN network with four convolutional layers and two fully connected layers and used their convolutional neural network to train 99 99 3 small patches, which were split from 3264 2248 road images collected by low-cost smartphones. The output of the network was the probability of whether a small patch was a crack or not. Their study shows that deep CNNs are superior to traditional machine learning techniques, such as SVM and boosting methods, in detecting pavement cracks. Pauly et al. [40] used a self-designed CNN model to study the relationship between network depth and network accuracy and proved the effectiveness of using a deeper network to improve detection accuracy in pavement crack detection based on computer vision. In contrast with [39], which used the same number of convolution kernels in all convolution layers, Nguyen et al. [41] used a convolution neural network with an increased number of convolution kernels in each layer because the features were more generic in the early layers and more original dataset specific in later layers [42]. Eisenbach et al. [43] presented the GAPs dataset, constructed a CNN network with eight convolution layers and three full connection layers, and analyzed the effectiveness of the state-of-the-art regularization techniques. However, its network input size was 64 64 pixels, which was too small to provide enough context information. The same problem also existed in [44,45,46].
Zhang et al. put forward CrackNet [52], which is an earlier study on pixel-level crack detection based on CNN. The prominent feature of CrackNet is using a CNN model without a pooling layer to retain the spatial resolution. Fei et al. have upgraded it to Cracknet-V [53]. While CrackNet and its series versions perform well, they are primarily used for 3D road crack images, and their performances on two-dimensional (2D) road crack images have not been validated. Fan et al. [3] proposed a pixel-level structured prediction method using CNN with full connections (FC) layers, but it has the disadvantage that it requires a long inference time for testing.